Made available in DSpace on 2014-12-17T13:57:02Z (GMT). No. of bitstreams: 1 FernandaLP_DISSERT.pdf: 5416443 bytes, checksum: 179175cb44c462129a12d10bfc036342 (MD5) Previous issue date: 2010-05-07 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / This research aims to study dimensions of urban life in the contemporaneous city. It is an effort to understand the functioning of the contemporary city as an artifact that somehow affects social relations. The study focuses on the limits and possibilities of urbanity in the city today, understanding urbanity as a set of factors that favor wealth, diversity and spontaneity of public life. The research aims to show that cities today tend to criate fragmented urban life into at least one of the three urbanity dimensions: spatial dimension, social and temporal dimension. The study involves the analysis of two public spaces in Fortaleza (Pra?a do Ferreira and the open urban public spaces of the Centro Cultural Drag?o do Mar), using Space Syntax Analysis methods and for Post Occupancy Evaluation procedures. Research shows that temporal dimension of urbanity is limited in the public spaces studied. In Pra?a do Ferreira, spatial and social dimensions are present, but their effects are limited by the temporal dimension. The Drag?o do Mar, on the other hand, the spatial and social dimensions of urban life are more limited and more concentrated in time / Esta pesquisa tem como objetivo geral estudar dimens?es da vida urbana na cidade atual. ? um esfor?o de compreens?o do funcionamento da cidade contempor?nea enquanto artefato que afeta de algum modo as rela??es sociais. O trabalho enfoca os limites e as possibilidades da urbanidade na cidade atual, entendendo-se urbanidade como um conjunto de fatores que favorecem a riqueza, a diversidade e a espontaneidade da vida p?blica. A pesquisa procura mostrar que as cidades atuais tendem a conformar uma vida urbana fragmentada em pelo menos uma das tr?s dimens?es da urbanidade: a dimens?o espacial, a dimens?o social e dimens?o temporal. Para tanto o trabalho envolve a an?lise de dois espa?os p?blicos da cidade de Fortaleza (a Pra?a do Ferreira e os espa?os abertos do Centro Cultural Drag?o do Mar), a partir da aplica??o de m?todos de An?lise Sint?tica do Espa?o e de procedimentos de Avalia??o P?s-ocupa??o. A pesquisa mostra que a dimens?o temporal da urbanidade ? limitada nos dois espa?os p?blicos estudados. No caso da Pra?a do Ferreira as dimens?es espacial e social est?o presentes, mas tem seu efeito limitado pela dimens?o temporal. No Drag?o do Mar, por outro lado, as dimens?es espacial e social da urbanidade s?o mais limitadas e mais concentradas em termos temporais

This dissertation can be broadly divided into two independent parts. The first three chapters analyse issues related to temporal and contemporaneous aggregation of econometric models. The fourth chapter contains an application of Bayesian techniques to investigate whether the post transition fiscal policy of Poland is sustainable in the long run and consistent with an intertemporal budget constraint.<p><p><p>Chapter 1 surveys the econometric methodology of temporal aggregation for a wide range of univariate and multivariate time series models. <p><p><p>A unified overview of temporal aggregation techniques for this broad class of processes is presented in the first part of the chapter and the main results are summarized. In each case, assuming to know the underlying process at the disaggregate frequency, the aim is to find the appropriate model for the aggregated data. Additional topics concerning temporal aggregation of ARIMA-GARCH models (see Drost and Nijman, 1993) are discussed and several examples presented. Systematic sampling schemes are also reviewed.<p><p><p>Multivariate models, which show interesting features under temporal aggregation (Breitung and Swanson, 2002, Marcellino, 1999, Hafner, 2008), are examined in the second part of the chapter. In particular, the focus is on temporal aggregation of VARMA models and on the related concept of spurious instantaneous causality, which is not a time series property invariant to temporal aggregation. On the other hand, as pointed out by Marcellino (1999), other important time series features as cointegration and presence of unit roots are invariant to temporal aggregation and are not induced by it.<p><p><p>Some empirical applications based on macroeconomic and financial data illustrate all the techniques surveyed and the main results.<p><p>Chapter 2 is an attempt to monitor fiscal variables in the Euro area, building an early warning signal indicator for assessing the development of public finances in the short-run and exploiting the existence of monthly budgetary statistics from France, taken as "example country". <p><p><p>The application is conducted focusing on the cash State deficit, looking at components from the revenue and expenditure sides. For each component, monthly ARIMA models are estimated and then temporally aggregated to the annual frequency, as the policy makers are interested in yearly predictions. <p><p><p>The short-run forecasting exercises carried out for years 2002, 2003 and 2004 highlight the fact that the one-step-ahead predictions based on the temporally aggregated models generally outperform those delivered by standard monthly ARIMA modeling, as well as the official forecasts made available by the French government, for each of the eleven components and thus for the whole State deficit. More importantly, by the middle of the year, very accurate predictions for the current year are made available. <p><p>The proposed method could be extremely useful, providing policy makers with a valuable indicator when assessing the development of public finances in the short-run (one year horizon or even less). <p><p><p>Chapter 3 deals with the issue of forecasting contemporaneous time series aggregates. The performance of "aggregate" and "disaggregate" predictors in forecasting contemporaneously aggregated vector ARMA (VARMA) processes is compared. An aggregate predictor is built by forecasting directly the aggregate process, as it results from contemporaneous aggregation of the data generating vector process. A disaggregate predictor is a predictor obtained from aggregation of univariate forecasts for the individual components of the data generating vector process. <p><p>The econometric framework is broadly based on Lütkepohl (1987). The necessary and sufficient condition for the equality of mean squared errors associated with the two competing methods in the bivariate VMA(1) case is provided. It is argued that the condition of equality of predictors as stated in Lütkepohl (1987), although necessary and sufficient for the equality of the predictors, is sufficient (but not necessary) for the equality of mean squared errors. <p><p><p>Furthermore, it is shown that the same forecasting accuracy for the two predictors can be achieved using specific assumptions on the parameters of the VMA(1) structure. <p><p><p>Finally, an empirical application that involves the problem of forecasting the Italian monetary aggregate M1 on the basis of annual time series ranging from 1948 until 1998, prior to the creation of the European Economic and Monetary Union (EMU), is presented to show the relevance of the topic. In the empirical application, the framework is further generalized to deal with heteroskedastic and cross-correlated innovations. <p><p><p>Chapter 4 deals with a cointegration analysis applied to the empirical investigation of fiscal sustainability. The focus is on a particular country: Poland. The choice of Poland is not random. First, the motivation stems from the fact that fiscal sustainability is a central topic for most of the economies of Eastern Europe. Second, this is one of the first countries to start the transition process to a market economy (since 1989), providing a relatively favorable institutional setting within which to study fiscal sustainability (see Green, Holmes and Kowalski, 2001). The emphasis is on the feasibility of a permanent deficit in the long-run, meaning whether a government can continue to operate under its current fiscal policy indefinitely.<p><p>The empirical analysis to examine debt stabilization is made up by two steps. <p><p>First, a Bayesian methodology is applied to conduct inference about the cointegrating relationship between budget revenues and (inclusive of interest) expenditures and to select the cointegrating rank. This task is complicated by the conceptual difficulty linked to the choice of the prior distributions for the parameters relevant to the economic problem under study (Villani, 2005).<p><p>Second, Bayesian inference is applied to the estimation of the normalized cointegrating vector between budget revenues and expenditures. With a single cointegrating equation, some known results concerning the posterior density of the cointegrating vector may be used (see Bauwens, Lubrano and Richard, 1999). <p><p>The priors used in the paper leads to straightforward posterior calculations which can be easily performed.<p>Moreover, the posterior analysis leads to a careful assessment of the magnitude of the cointegrating vector. Finally, it is shown to what extent the likelihood of the data is important in revising the available prior information, relying on numerical integration techniques based on deterministic methods.<p> / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Infrastructure is presenting significant national and global challenges. Whilst often seen as performing well, infrastructure tends to do so against only limited terms of reference and short-term objectives. Given that the world is facing a new infrastructure bill of ~£40T, improving the benefits delivered by existing infrastructure is vital (Dobbs et al., 2013). This thesis investigates strategic intent and the management of infrastructure systems; how factors such as organisational structure and business practice affect outcomes and the ways in which those systems — not projects — are managed. To date, performance has largely been approached from the perspective of project investment and/or delivery, or the assessment of latent failures arising from specific shocks or disruptive events (e.g. natural disaster, infrastructure failures, climate change). By contrast, the delivery of system-level services and outcomes across the infrastructure system has been rarely examined. This is where infrastructure forms an enduring system of services, assets, projects, and networks each at different stages of their lifecycle, and affecting one another as they develop, then age. Yet system performance, which also includes societal, organisational, administrative and technical factors, is arguably the level relevant to, and the reality of, day-to-day public infrastructure management. This research firstly investigated industry perceptions in order to test and confirm the problem: the nub of which was the inability to fully deliver appropriate and relevant infrastructure outcomes over the long term. Three detailed studies then explored the reasons for this problem through different lenses; thereby providing an evidence-base for a range of issues that are shared by the wider infrastructure industry. In confirming its hypothesis that “the strategic intent and the day-to-day management of infrastructure systems are often misaligned, with negative consequences for achieving the desired long-term infrastructure system outcomes”, this research has increased our understanding of the ways in which that misalignment occurs, and the consequences that result. It found those consequences were material, and frequently not visible within the sub-system accountable for the delivery of those outcomes. That public infrastructure exists, not in its own right, but to be of benefit to society, is a central theme drawn from the definition of infrastructure itself. This research shows that it is not enough to be focused on technical outcomes. Infrastructure needs to move beyond how society interacts with an asset, to the outcomes that reflect the needs, beliefs, and choices of society as well as its ability to respond to change (aptitude). Although the research has confirmed its hypothesis and three supporting propositions, the research does not purport to offer ‘the solution’. Single solutions do not exist to address the challenges facing a complex adaptive system such as infrastructure. But the research does offer several system-oriented sense-making models at both the detailed and system-level. This includes the probing methodology by way of a diagnostic roadmap. These models aim to assist practitioners in managing the transition of projects, assets, and services into a wider infrastructure system, their potential, and in (re)orienting the organisation to the dynamic nature of the system and its societal imperative.